This research would represent the first national study of multiple parameters of financial conflicts-of-interest, and how they may be correlated with practices thought to impact the integrity of research. Data from this project would inform the committee of new policy recommendations by identifying, for the first time, those arrangements that are associated with, or which best predict when an investigator may engage in conduct that may impact the integrity of research. This will allow for a better allocation of future resources to address those arrangements that are in the greatest need of regulatory oversight and/or educational initiatives. The research is innovative, in that the focus is on practices of investigators, rather than upon institutional policies, and would provide the first national data on financial conflicts-of-interest in both the medical and nursing school settings. Industry-funded research is the sole focus of this proposal. National surveys of life-science faculty at medical and nursing schools will be conducted to accomplish the following specific aims: 1) Determine A) the national prevalence of various financial arrangements undertaken by investigators, that may constitute a financial conflict of interest; B) determine the national prevalence of various, questionable practices in the conduct and reporting of research; and C) survey investigator knowledge of policies governing financial conflicts-of-interest. Frequencies and descriptive statistics will be prepared for each relevant survey question, and will be reported taking into account the margin of error. 2) Determine if there is any difference between nursing and medical schools in A) the prevalence of financial arrangements that can give rise to conflicts-of-interest; B) in the prevalence of questionable integrity practices; and C) in the investigator knowledge of policies governing financial conflicts-of-interest. 3) Determine which financial arrangements are associated with specific, questionable integrity practices. Chi square tests will be used to ascertain the statistical significance of relationships between categorical questions. T-tests will be used to test for differences in means where appropriate. 4) Explore the utility of using data reduction techniques and appropriate, multi-variate modeling techniques to show which types of financial arrangements predict questionable integrity practices.